Generating support material for three-dimensional printing

ABSTRACT

In one embodiment of the present invention, a support structure generator creates support structures designed to buttress three-dimensional (3D) digital models during 3D printing. In operation, the support structure generator incrementally constructs a support graph that connects overhanging points included in the 3D model with support points on a horizontal ground plane or relatively flat surfaces in the 3D model. After generating the 3D model, the support structure generator translates the connections between the nodes into support posts sized to sufficiently support the connected surfaces with the minimum amount of support material. Advantageously, the support structure is noticeably sparser than conventional support structures that fill a given support region with a solid volume of support material. Consequently, the time necessary for 3D printers to fabricate the support structure of interconnected support posts is less than the time required for 3D printers to fabricate conventional support structures.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of the U.S. Provisional PatentApplication having Ser. No. 61/911,311, filed on Dec. 3, 2013, which ishereby incorporated herein by reference.

BACKGROUND OF THE INVENTION

Field of the Invention

Embodiments of the present invention relate generally to computerprocessing and, more specifically, to generating support material forthree-dimensional printing.

Description of the Related Art

A typical three-dimensional (3D) printer generates a 3D solid objectbased on a 3D printable digital model, such as a 3D mesh of triangles.In operation, the 3D printer creates the 3D object from bottom to top.For instance, if the digital model were to represent a candy cane, thenthe 3D printer would print successive layers of material beginning witha layer corresponding to the bottom of the stem and ending with a layercorresponding to the top of the hook. To avoid subsequent un-supportedlayers (such as the hook of a candy-cane) collapsing and/or droopingonto proceeding layers or the ground due to gravity during the printingprocess, 3D printers typically generate bloated 3D objects.

Such bloated 3D objects include not only material that represents the 3Dobject but also “support structures” that ensure the integrity of thematerial that forms the 3D object throughout the 3D printing process.Often, the 3D printer generates support structures in a different typeof material (support material) than the material used to generate thegeometries associated with the 3D object. After the 3D printer generatesthe bloated 3D object, then a designer performs post-processingoperations to remove the now-extraneous support material and reveal thedesired 3D object. For instance, the designer may break off or dissolvethe support material.

In one approach to generating support material, the 3D printer firstidentifies overhanging surfaces of the 3D model that require support.The 3D printer then projects these overhanging surfaces to the ground,creating projected regions. Finally, the 3D printer fills the volumebetween each overhanging surface and the corresponding projected regionwith support material. Again, after the 3D printer has generated the 3Dmodel, the support material is superfluous.

One limitation to filling volumes with support material is thatgenerating the support material is time consuming. Consequently,fabricating volumes of support material between overhanging surfaces andthe ground may increase the execution time of the 3D printer tounacceptable levels. Further, the support material is often costly. Ingeneral, as the amount of support material that the 3D printer generatesincreases, the cost-effectiveness of 3D printing decreases.

As the foregoing illustrates, what is needed in the art are moreeffective techniques for generating support material for 3D printing.

SUMMARY OF THE INVENTION

One embodiment of the present invention sets forth acomputer-implemented method for generating a plurality of support postsimplemented when printing three-dimensional models. The method includesidentifying a first overhanging surface in a three-dimensional modelbased on a maximum overhang threshold, where the first overhangingsurface includes a first contact point and a second contact point;generating a first set of support posts that connects the first contactpoint to a first support point; and generating a second set of supportposts that connects the second contract point to a second support point,where no post included in the second set of support posts intersects thefirst contact point.

One advantage of disclosed approach is that the support posts enableefficient implementation of 3D models without risking defectsattributable to gravity. Notably, the support posts effectively buttressthe 3D model using less support material than conventional supportstructures that fill support regions with a solid volume of supportmaterial. Advantageously, reducing the amount of generated supportmaterial reduces both the quantity of support material and the timerequired for a 3D printer to print robust 3D objects.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentinvention can be understood in detail, a more particular description ofthe invention, briefly summarized above, may be had by reference toembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate onlytypical embodiments of this invention and are therefore not to beconsidered limiting of its scope, for the invention may admit to otherequally effective embodiments.

FIG. 1A is a block diagram illustrating a computer system configured toimplement one or more aspects of the present invention;

FIG. 1B is a block diagram illustrating a three-dimensional (3D)printing system controlled by the computer system of FIG. 1A andconfigured to implement one or more aspects of the present invention;

FIG. 2A is a conceptual diagram illustrating how the three-dimensional(3D) model interactive tool of FIG. 1A may be configured to process aninitial 3D mesh, according to one embodiment of the present invention;

FIG. 2B is a conceptual diagram illustrating how the overhang analysisengine of FIG. 1B may be configured to compute the overhang shading forthe current three-dimensional (3D) mesh of FIG. 2A, according to oneembodiment of the present invention;

FIG. 3A illustrates the overhang angle thresholds and the dynamicallyupdated visualizations, according to one embodiment of the presentinvention;

FIG. 3B illustrates the initial three-dimensional (3D) mesh, the current3D mesh, and the dynamically updated visualizations, according to oneembodiment of the present invention;

FIG. 4 is a flow diagram of method steps for computing and interactivelydisplaying overhang data for a three-dimensional (3D) mesh, according toone embodiment of the present invention;

FIG. 5 is a conceptual diagram illustrating a three-dimensional (3D)model with highlighted overhangs and a corresponding 3D model withsupport geometry, according to one embodiment of the present invention;

FIG. 6 is a conceptual diagram illustrating the incremental graphgenerator of FIG. 1B, according to one embodiment of the presentinvention;

FIG. 7 is a conceptual diagram illustrating selection scenarios that theend point selector of FIG. 1 may be configured to evaluate, according toone embodiment of the present invention;

FIGS. 8A-8B set forth a flow diagram of method steps for generatingsupport geometry to facilitate printing of a three-dimensional (3D)model, according to one embodiment of the present invention; and

FIG. 9 is a flow diagram of method steps for selecting an optimized endpoint for a support structure that facilitates printing of athree-dimensional (3D) model, according to one embodiment of the presentinvention.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth toprovide a more thorough understanding of the present invention. However,it will be apparent to one of skill in the art that the presentinvention may be practiced without one or more of these specificdetails.

System Overview

FIG. 1A is a block diagram illustrating a computer system 100 configuredto implement one or more aspects of the present invention. As shown, thecomputer system 100 includes, without limitation, a central processingunit (CPU) 170, a system memory 150, a graphics processing unit (GPU)172, input devices 112, and a display device 114.

The CPU 170 receives input user input information from the input devices112, such as a keyboard or a mouse. In operation, the CPU 170 is themaster processor of the computer system 100, controlling andcoordinating operations of other system components. In particular, theCPU 170 issues commands that control the operation of the GPU 172. TheGPU 172 incorporates circuitry optimized for graphics and videoprocessing, including, for example, video output circuitry. The GPU 172delivers pixels to the display device 114 that may be any conventionalcathode ray tube, liquid crystal display, light-emitting diode display,or the like. In various embodiments, GPU 172 may be integrated with oneor more of other elements of FIG. 1A to form a single system. Forexample, the GPU 172 may be integrated with the CPU 170 and otherconnection circuitry on a single chip to form a system on chip (SoC).

The system memory 174 stores content, such as software applications anddata, for use by the CPU 170 and the GPU 172. As shown, the systemmemory 174 includes a 3D model generator 110, a 3D model interactivetool 120, and a support geometry generator 130. The 3D model generator310, the 3D model interactive tool 120 and the support geometry 130 aresoftware applications that execute on the CPU 170, the GPU 172, or anycombination of the CPU 170 and the GPU 172. Both the 3D modelinteractive tool 120 and the support geometry generator 130 facilitate3D printing.

The 3D model generator 110 enables specification of a 3D model 117. The3D model interactive tool 120 dynamically identifies “overhanging”geometries in the 3D model 117 that exceed an overhang angle thresholdsupported by a 3D printer 150. The support geometry generator 130creates support geometry 140 that reinforces the overhanging geometriesin the 3D model 117. In alternate embodiments, the system memory 174 maynot include the 3D model generator 110, the 3D model interactive 120tool and/or the support geometry generator 130. In other embodiments,the 3D model generator 110, the 3D model interactive tool 120 and/or thesupport geometry generator 130 are integrated into any number (includingone) of software applications. In some embodiments, the 3D modelgenerator 110, the 3D model interactive tool 120 and/or the supportgeometry generator 130 may be provided as an application program (orprograms) stored on computer readable media such as a CD-ROM, DVD-ROM,flash memory module, or other tangible storage media.

The components illustrated in the computer system 100 may be included inany type of computer system 100, e.g., desktop computers, servercomputers, laptop computers, tablet computers, and the like.Additionally, software applications illustrated in computer system 100may execute on distributed systems communicating over computer networksincluding local area networks or large, wide area networks, such as theInternet. Notably, the 3D model interactive 120 tool and the supportgeometry generator 130 described herein are not limited to anyparticular computing system and may be adapted to take advantage of newcomputing systems as they become available.

It will be appreciated that the computer system 100 shown herein isillustrative and that variations and modifications are possible. Thenumber of CPUs 170, the number of GPUs 172, the number of systemmemories 174, and the number of applications included in the systemmemory 174 may be modified as desired. Further, the connection topologybetween the various units in FIG. 1A may be modified as desired.

FIG. 1B is a block diagram illustrating a three-dimensional (3D)printing system 101 controlled by the computer system 100 of FIG. 1A andconfigured to implement one or more aspects of the present invention. Asshown, the 3D printing system 101 includes, without limitation, the 3Dmodel generator 110, the 3D model interactive tool 120, the supportgeometry generator 130, the 3D printer 150, and a 3D support remover160. As shown in FIG. 1A, the 3D model generator 110, the 3D modelinteractive tool 120, and the support geometry generator 130 areincluded in the system memory 174 of the computer system 100 and executeon the CPU 170 and/or the GPU 172.

In operation, the 3D model generator 110 enables specification of the 3Dmodel 117. The 3D model 117 describes a desired 3D solid object. The 3Dmodel generator 110 may be implemented in any technically feasiblefashion. For instance, the 3D model generator 110 may include computeraided design (CAD) software. Such CAD software often includes agraphical user interface that converts designer input such as symbolsand brush stroke operations to geometries in the 3D model 117.Alternatively the 3D model generator 110 may be a 3D scanner thatanalyzes an existing 3D solid object to create the 3D model 117 as adigital template for creation of copies of the existing 3D solid object.

The 3D model 117 may conform to any 3D printable format as known in theart. For instance, in some embodiments the 3D model 117 may capture unitnormal and vertices that define the 3D solid object in thestereolithograpy format. In alternate embodiments, the3D model 117 maycapture a 3D mesh of interconnected triangles that define the 3D solidobject in the collaborative design activity (COLLADA) format. Inalternate embodiments, the 3D model 117 is created manually and the 3Dmodel generator 110 is not included in the 3D printing system 101.

As shown, the 3D model generator 110 is coupled to the 3D modelinteractive tool 120. This coupling may be implemented in anytechnically feasible fashion, such as exporting the 3D model 117 fromthe 3D model generator 110 and then importing the 3D model 117 to the 3Dmodel interactive tool 120. As also shown, the 3D model interactive tool120 includes, without limitation, a 3D model graphical user interface(GUI) 122 and an overhang analysis engine 124.

The 3D model GUI 122 is configured to receive designer input informationfrom input devices 112, such as a keyboard or a mouse. After the 3Dmodel interactive tool 120 processes the designer input information inconjunction with the 3D model 117, the 3D model GUI 122 delivers pixelsto a display device 114 that may be any conventional cathode ray tube,liquid crystal display, light-emitting diode display, or the like. The3D model interactive tool 120 is configured to continuously repeat thiscycle, enabling the designer to dynamically interact with the 3D model117 based on corresponding images on the display device 110.

As part of the 3D printing process, designers often “eye-ball” the 3Dmodel 117 in an effort to estimate where the support geometry generator130 is likely to insert support material to reduce the probability ofthe sagging during bottom-to-top 3D object creation. Advantageously, theoverhang analysis engine 124 includes functionality that accuratelycomputes the angles of surfaces in the 3D model 117 relative to thehorizontal print bed. Further, the overhang analysis engine 124 workstogether with the 3D model GUI 122 to highlight surfaces in the 3D model117 that exceed a maximum overhang threshold (not shown in FIG. 1B).Typically the maximum overhang threshold is the maximum angle that the3D printer 150 is configured to print without requiring supportmaterial.

Based on this visual feedback, the designer may elect to redesign the 3Dmodel 117 to reduce angles or integrate designer-defined supportmaterial in discrete locations. Further, the designer may elect toreplace the 3D printer 150 with a different 3D printer that isassociated with a different maximum overhang threshold. Or the designermay adjust any safety margin incorporated into the maximum overhangthreshold. Notably, the overhang analysis engine 124 and the 3D modelGUI 122 continually update the overhang data and the image sent to thedisplay device 114 to reflect any changes. Because updates aredynamically reflected in the displayed and highlighted 3D model 117, thedesigner may efficiently evaluate the impact of various modifications tothe 3D model 117 and the 3D printer 150 on the quality of the 3D object.

As shown, the 3D model interactive tool 120 is coupled to the supportgeometry generator 130. The coupling may be implemented in anytechnically feasible fashion, such as exporting the 3D model 117 fromthe 3D model interactive tool 120 and then importing the 3D model 117 tothe support geometry generator 130. In alternate embodiments, the 3Dmodel interactive tool 120 is omitted from the 3D printing system 101,and the 3D model generator 110 is coupled directly to the supportgeometry generator 130.

The support geometry generator 130 creates the support geometry 140 thatreinforces the 3D model 117. Notably, the support geometry 140 enablesthe 3D printer 150 to efficiently and cost-effectively fabricate the 3Dobject without incurring defects attributable to the effects of gravityduring the printing process. To reduce the amount and extent of thesupport geometry 140, the support geometry generator 130 incrementallygenerates the support geometry 140 as a series of support posts.Together, these support posts buttress surfaces in the 3D model 117 thatexceed the maximum overhang threshold. Again, typically the maximumoverhang threshold is the maximum angle that the 3D printer 150 mayprint without risking gravity-related defects.

The support geometry generator 130 includes, without limitation, anincremental graph generator 138, an angle analyzer 132, and an end pointselector 134. The incremental graph generator 138 generates a supportgraph (not shown in FIG. 1B) that serves as a blueprint for the supportgeometry 140. More specifically, the support graph includes nodes andedges, where each node corresponds to a different point in 3D space, andeach edge represents the connection of two points via a support post.

In operation, the incremental graph generator 138 sequentially addsedges to the support graph—starting from each point in the 3D model 117that requires support and growing the support graph downwards in 3Dspace. As part of this incremental building process, the angle analyzer132 evaluates the relationships between various surfaces in the 3D model117, the dynamically growing support graph, and/or the ground (i.e., the3D printing surface). For each edge, the end point selector 134evaluates various end points and then chooses an end point for the edgethat optimizes the length and orientation of the support postrepresented by the edge to streamline the overall support geometry 140.

The 3D printer 150 is any device capable of additively printing a 3Dobject based on the 3D model 117. The 3D printer may be configured tobuild-up any type of 3D object in any technically feasible fashion. Forinstance, in some embodiments, the 3D printer 150 extrudes plastic, andthe 3D printer 150 may be configured to print plastic replacement partsfor tools based on blueprints expressed as 3D models 117. In otherembodiments, the 3D printer 150 generates live cells, and the 3D printer150 may be configured to print organs, such as kidneys. The supportgeometry 140 ensures that each successive layer of the 3D objectreceives the support required to prevent gravity-induced defects, herebyensuring the integrity of the 3D object throughout the 3D printingprocess.

After the 3D printer 150 generates the top layer of the 3D object, thesupport geometry 140 is unnecessary and typically detracts from theaesthetic appeal and/or functionality of the 3D object. The 3D supportremover 160 performs removal operations that separate the supportmaterial from the 3D object, thereby revealing the 3D object specifiedby the 3D model 117 unencumbered by the constraints of the manufacturingprocess. In some embodiments, the 3D support remover 160 is a human whomanually cuts away or peels off the support material. In otherembodiments, the 3D support material is water soluble, and the 3Dsupport remover 160 is a bath of water.

Irrespective of the type of the 3D support remover 160, the areas wheresupport material are removed from the 3D object often exhibit undesireddefects, such as rough textures or small marks on the surface of the 3Dobject. Again, the 3D model interactive tool 120 enables designers toeffectively r educe the extent and/or optimize the location of thesupport geometry 140. Consequently, the overall quality of the 3D objectis increased compared to 3D objects generated using conventional 3Dprinting systems. Further, the support geometry generator 130 minimizesthe amount and extent of the support geometry 140 compared to conventiontechniques that fill entire volumes with support structures. Thus, theoverall efficiency of the 3D printer 150 is increased compared to 3Dprinters operating in conventional 3D printing systems.

It will be appreciated that the system shown herein is illustrative andthat variations and modifications are possible. The connection topology,including the number and arrangement of the 3D model generator 110, the3D model interactive tool 120, the support geometry generator 130, the3D printer 150, and the 3D support remover 160, may be modified asdesired. In certain embodiments, one or more components shown in FIGS.1A and 1B may not be present. For instance, both the 3D model generator110 and the 3D model interactive tool 120 could be eliminated, and thesupport geometry generator 130 could receive a manually created file asinput.

Lastly, the 3D model interactive tool 120 and the support geometrygenerator 130 may be implemented in any combination of software andhardware units. In some embodiments the angle analyzer 132 may beremoved and the associated functionality may be incorporated into one ormore different units. In other embodiments, the endpoint selector 134may be removed and/or the associated functionality may be incorporatedinto one or more different units, including the incremental graphgenerator 138.

Identifying and Displaying Overhanging Regions

FIG. 2A is a conceptual diagram illustrating how the three-dimensional(3D) model interactive tool 120 of FIG. 1B may be configured to processan initial 3D mesh 205, according to one embodiment of the presentinvention. In general, the 3D model interactive tool 120 facilities thevisual analysis of the initial 3D mesh 205 and any subsequentmodifications to the initial 3D mesh 205, such as a current 3D mesh 235.Notably, the 3D model interactive tool 120 enables efficient andeffective graphical portrayal of locations where the 3D printer 140 isconfigured to insert support material.

As shown, the 3D model interactive tool 120 includes, withoutlimitation, the 3D model GUI 122 of FIG. 1B, the overhang analysisengine 124 of FIG. 1B, and a diffuse shader 280. The 3D model GUI 122coordinates input and output operations associated with the 3D modelinteractive tool 120. In general, the 3D model GUI 122 supports importsof different types of 3D models 117, display settings, analysissettings, and the routing of output graphical information to the displaydevice 114.

As also shown, the 3D model GUI 122 includes, without limitation, 3Dmesh modification tools 222 and an overhang angle threshold selector224. In operation, the 3D model GUI 122 receives the initial 3D mesh 205and establishes the initial 3D mesh 205 as a current 3D mesh 235. Uponreceiving changes via the 3D mesh modification tools 222, the 3D modelGUI updates the current 3D mesh 235. In alternate embodiments, anytechnically feasible fashion and/or format for conveying information ina 3D printable form may replace the initial 3D mesh 205 and/or thecurrent 3D mesh 235.

As described in greater detail in conjunction with FIG. 2B, the overhanganalysis engine 124 performs overhang computations based on the current3D mesh 235 and an overhang angle threshold 231 that the designerspecifies via the overhang angle threshold selector 224. In someembodiments, the designer sets the overhang angle threshold 231 to matchthe maximum angle of a local surface patch relative to the horizontalprint bed that the 3D printer 140 is configured to print without addingsupport material. In alternate embodiments, the designer sets theoverhang angle threshold 231 to the sum of this 3D printer 140 maximumangle and a “safety” margin. In yet other embodiments, the designer setsthe overhang angle threshold 231 based on the characteristics of adifferent 3D printer to explore the impact of replacing the 3D printer140 with the different 3D printer.

The overhang angle threshold selector 224 may be implemented in anytechnically feasible fashion. In some embodiments, the overhang anglethreshold selector 224 is implemented as a graphical slider that thedesigner manipulates to set the overhang angle threshold 231. In otherembodiments, the overhang angle threshold selector 224 is a parameterincluded in a graphical designer-modifiable list of parameters. In yetother embodiments, the overhang angle threshold selector 224 may beimplemented as a parameter included in a configuration file or maybehard-coded as a parameter associated with the 3D printer 140.

After receiving and analyzing the current 3D mesh 235 in conjunctionwith the overhang angle threshold 231, the overhang analysis engine 124generates an overhang shading 251 based on this analysis. This overhangshading 251 visually emphasizes areas in the current 3D mesh 235 wherethe angle exceeds the overhang angle threshold 231. Further, theoverhang shading 251 depicts the relative degree to which angles exceedthe overhang angle threshold 231. For instance, suppose that theoverhang analysis engine 124 were configured to generate overhangingshading 251 with blends of white (corresponding to angles less than theoverhang angle threshold 231) and red. Further, suppose that one anglewere to exceed the overhang angle threshold 231 by 30 degrees, andanother angle were to exceed the overhang angle threshold 231 by 10degrees. In such a scenario, the overhang analysis engine 125 wouldgenerate overhang shading 251 in which the location associated with thefirst angle was represented by a predominantly red shade, and thelocation associated with the second angle was represented by apredominantly white shade.

Subsequently, the diffuse shader 280 processes the overhang shading 251in conjunction with the current 3D mesh 235, generating a compositeshading 281. The diffuse shader 280 computes diffuse shading across thecurrent 3D mesh 235 using any technique as known in the art. The diffuseshader 280 then applies this diffuse shading to the overhang shading251. The resulting composite shading 281 reflects both the colorspecified by the current 3D mesh 235 and the color of the overhangshading 251. In alternate embodiments, the diffuse shader 280 maycompute other shading (e.g., ambient shading, specular shading, etc.) inaddition to the diffuse shading. In such embodiments, the diffuse shader280 performs operations that integrate additional shading componentsinto the composite shading 251.

The 3D model GUI 122 receives the composite shading 251 and includesthis information in the dynamically updated visualization 291—creatingan annotated version of the current 3D mesh 235. The 3D model GUI 122then transmits the dynamically updated visualization 291 to the displaydevice 114 of FIG. 1A. As disclosed previously herein, initially thecurrent 3D mesh 235 corresponds to the initial 3D mesh 205. However, the3D model GUI 122 supports changes to the current 3D mesh 235 via the 3Dmesh modification tools 222. Consequently, the current 3D mesh 235 mayevolve throughout time.

Further, the overhang angle threshold selector 224 supports changes tothe overhang angle threshold 231. For instance, after inspecting thedynamically updated visualization 291, the designer may performsmoothing operations via a brush included in the 3D mesh modificationstools 222 to reduce one or more of the highlighted overhangs.Alternatively, the designer may add a support column using the 3D meshmodifications tools 222, thereby controlling the structure of thesupport material required for manufacturing. In yet other circumstances,the designer may elect to decrease a safety margin included in theoverhang angle threshold 231 In such a scenario, the designer may adjustthe overhang angle threshold selector 224 to specify a larger value forthe overhang angle threshold 231.

After the 3D model GUI 122 receives modifications to the current 3D mesh235 and/or the overhang angle threshold selector 224, the overhanganalysis engine 124 and the diffuse shader 280 re-compute the overhangshading 251 and the composite shading 281 respectively. Subsequently,the 3D model GUI 122 re-generates the dynamically updated visualization291, and the display device 114 refreshes the displayed image according.Advantageously, this automated analysis-display loop enables thedesigner to quickly ascertain the impact of changes to the current 3Dmesh 235 and/or the overhang angle threshold 231.

As previously disclosed herein, the 3D model interactive tool 120 may beimplemented in any technically feasible fashion in any combination ofsoftware and hardware. For example, one or more computations performedby the overhang analysis engine 124 may be performed by a graphicsprocessing unit (GPU) shading unit. Similarly, the diffuse shader 280may be implemented as a GPU shading unit. In alternate embodiments, thefunctionality described herein may be distributed in any manner acrossany number of different units. For instance, in some embodiments, theoverhang shading 251 and diffuse shading operations are performed by asingle composite shading unit.

FIG. 2B is a conceptual diagram illustrating how the overhang analysisengine 124 of FIG. 1B may be configured to compute the overhang shading251 for the current three-dimensional (3D) mesh 235 of FIG. 2A,according to one embodiment of the present invention. As shown, theoverhang analysis engine 124 includes, without limitation, a surfacenormal analyzer 310, an angle comparator 330, and an overhang shader350.

In operation, the surface normal analyzer 310 processes the current 3Dmesh 235 and generate dot products 315. In particular, surfaces includedin the current 3D mesh 235 are represented as one or more triangles (notshown). For each of these triangles, the surface normal analyzer 310determines the surface normal of the triangle. The surface normalanalyzer 310 then performs a per-triangle dot product operation betweenthe corresponding surface normal and the up-axis vector, generating thedot product 315 for the triangle. As persons skilled in the art willrecognize, the dot products 315 represent the angle of the trianglesrelatively to the horizontal print bed of the 3D printer 140.Consequently, the dot products 315 correlate to the generation ofsupport material by the 3D printer 140.

The angle comparator 330 performs comparison operations between the dotproducts 315 and the overhang angle threshold 231 of FIG. 2A. For eachof the dot products 315, if the dot product 315 exceeds the overhangangle threshold 231, then the angle comparator 330 considers thetriangle associated with the dot product 315 to be overhanging. Further,the magnitude of the dot product 315 corresponds to the significance ofthe overhang. After performing the comparison operations, the anglecomparator 330 scales the dot products 315 to overhang magnitudes 325that range in value between zero and one. If the angle comparator 330does not consider a particular triangle to be overhanging, then theangle comparator 330 sets the value of the corresponding overhangmagnitude 335 to zero. By contrast, the angle comparator 330 translatesthe largest magnitude dot products 315 to overhang magnitudes 335 ofone. In alternate embodiments, the angle comparator 330 may beconfigured to perform any type of operation that yields deterministicinformation regarding the relative significance of overhangs in thecurrent 3D mesh 235.

Upon receiving the overhang magnitudes 335, the overhang shader 350applies an overhang color map 310 to the overhang magnitudes 335,thereby generating the overhang shading 251. The overhang shading 251facilitates the concise transmission of overhang data to the designervia the dynamically updated visualization 291. More specifically, foreach triangle, the overhang shading 251 includes a color that is basedon the overhang magnitude 335 associated with the triangle. The overhangcolor map 301 may be conveyed in any technically feasible fashion andmay encode the overhang magnitude 335 in any designer-friendly manner.For instance, the color map 310 may map overhang magnitudes 335 of zeroto white, overhang magnitudes 335 of one to red, and other overhangmagnitudes 335 to a blend of red and white.

Note that the techniques described herein are illustrative rather thanrestrictive, and may be altered without departing from the broaderspirit and scope of the invention. In particular, alternate embodimentsinclude any techniques that automatically generate any type of overhangangle information for 3D printing analysis and/or graphically displaysuch overhang angle information. Notably, alternate embodiments may ormay not include modification functionality and configurability.

In alternate embodiments, the current 3D mesh 235 may be replaced withany type of 3D model 117 and may or may not represent the 3D object astriangles. Further, the surface normal analyzer 310, the anglecomparator 330, and the overhang shader 350 may be configured to operateon any type of 3D model 117 at any level of granularity (e.g., per-pointinstead of per-triangle). The functionality included in the overhanganalysis engine 124 may be implemented in any combination of softwareand hardware and divided into any number of discrete units. Forinstance, in alternate embodiments the functionality of the surfacenormal analyzer 310, the angle comparator 330, and the overhang shader350 may be implemented in a single shader that executes on a graphicsprocessing unit (not shown).

FIG. 3A illustrates the overhang angle thresholds 231-0 and 231-1 andthe dynamically updated visualizations 291-0 and 291-1, according to oneembodiment of the present invention. Both the dynamically updatedvisualizations 291-0 and 291-1 depict the same current 3D mesh235—representing a solid bunny. However, the dynamically updatedvisualization 291-0 reflects the overhand shading 251-0 associated withthe overhang angle threshold 231-0 equal to 45 degrees. And thedynamically updated visualization 291-1 reflects the overhang shading251-1 associated with the overhang angle threshold 231-1 equal to 83degrees.

The overhang shading 251-0 and 251-1 communicate the significance ofoverhangs via the relative “redness” of highlights included in thedynamically updated visualizations 291-0 and 291-1 respectively. Becausethe overhang angle threshold 231-0 is lower than the overhang anglethreshold 231-1, the areas of the dynamically updated visualization291-0 that exhibit redness are more extensive than the areas of thedynamically updated visualization 291-1 that exhibit redness. FIG. 3Aillustrates how the 3D model interactive tool 120 enables designers toquickly and effectively explore the impact of the different overhangangle thresholds 231 on the quality of the 3D model 117. For example,designers may vary the overhang angle threshold 231 to correspond todifferent potential 3D printers and then compare the overhang shadings251 depicted in the corresponding dynamically updated visualizations 291to judiciously select the 3D printer 140 that is included in the 3Dprinting system 101.

FIG. 3B illustrates the initial three-dimensional (3D) mesh 205, thecurrent 3D mesh 235, and the dynamically updated visualizations 291-2and 291-3, according to one embodiment of the present invention. Theoverhang angle threshold 231 (not shown in FIG. 3B) that corresponds todynamically updated visualization 291-2 is equal to the overhang anglethreshold 231 that corresponds to the dynamically updated visualization291-3.

For explanatory purposes only, the context of FIG. 3B is that thedesigner generates the initial 3D mesh 205 via the 3D model generator110. The 3D model interactive tool 120 receives the initial 3D mesh 205,the overhang analysis engine 124 generates the overhang shading 251-2,and the 3D model GUI 122 relays the dynamically updated visualization291-2 to the display device 114. As shown, the display device 114 thenexhibits a bunny annotated based on the significance of overhangs. Theoverhangs are highlighted as shades of red based on the overhangingshading 251-2.

The designer then contemplates the surfaces highlighted as overhangs inthe dynamically updated visualization 291-2. Based on this visualinspection, the designer determines that, if the 3D printer 140 were togenerate the bunny based on the initial 3D mesh 205, then the 3D printer140 would generate an unacceptable amount and/or location of supportmaterial.

To increase the quality of the final 3D object, the designerstrategically modifies the initial 3D mesh 205, creating the current 3Dmesh 235. In particular, the designer applies a brush included in the 3Dmesh modification tools 222 to add material underneath the chin of thebunny, thereby reducing the angles of the surfaces in the chin to belowthe overhang angle threshold 231. The overhang analysis engine 124 thengenerates the overhang shading 251-3 corresponding to the current 3Dmesh 235. Subsequently, the 3D model GUI 122 annotates the current 3Dmesh 235 with the overhang shading 251-3, generating the dynamicallyupdated visualization 291-3. And the display device 114 exhibits thedynamically updated visualization 291-3 instead of the previousdynamically updated visualization 291-2.

As shown, the dynamically updated visualization 291-3 depicts the bunny,but the expanded chin surfaces are no longer highlighted as overhanging.The designer is satisfied with the impact of the modifications, and the3D printer 140 generates a bloated 3D object based on the current 3Dmesh 235. Notably, this bloated 3D object includes the desired 3D object(the bunny) along with support structures. Advantageously, there are nosupport structures in the chin region of the bunny. Finally, the 3Dsupport remover 150 separates the support material from the non-supportmaterial, revealing the desired 3D object (i.e., the bunny) withoutdefects in the chin region.

As the example in FIG. 3B illustrates, the 3D model interactive tool 120enables designers to quickly and effectively explore the impact of themodifications to the initial 3D mesh 205. In alternate embodiments,suppose that the designer were to determine, based the dynamicallyupdated visualization 291-2 corresponding to the current 3D mesh 325,that the modifications would not cause the desired reduction inoverhangs. In such a scenario, the designer could repeat thismodification-analysis cycle until the designer determined that thecurrent 3D mesh 235 would cause the desired reductions in overhangs. Inthis fashion, the designer can interactively optimize the current 3Dmesh 235 to ensure that aesthetic and/or functional requirements for the3D object are attained.

FIG. 4 is a flow diagram of method steps for computing and interactivelydisplaying overhang data for a three-dimensional (3D) mesh, according toone embodiment of the present invention. Although the method steps aredescribed with reference to the systems of FIGS. 1-5, persons skilled inthe art will understand that any system configured to implement themethod steps, in any order, falls within the scope of the presentinvention.

As shown, a method 400 begins at step 402, where the 3D model GUI 122receives the initial 3D mesh 205 and sets the current 3D mesh 235 to theinitial 3D mesh 205. As part of step 402, the 3D model GUI 122determines the overhang angle threshold 231 based on the overhang anglethreshold selector 224. The overhang angle threshold selector 224 may beimplemented in any technically feasible fashion—such as a graphicalslider that enables the designer to easily adjust the overhang anglethreshold 231. The 3D model GUI 122 transmits the current 3D mesh 2325and the overhang angle threshold 231 to the overhang analysis engine214.

At step 404, the surface normal analyzer 310 included in the overhanganalysis engine 124 computes the dot products 315 between surfacenormals corresponding to the current 3D mesh 235 and the up direction.Notably, the surface normal analyzer 310 determines the surface normalsper-triangle. In alternate embodiments, the surface normal analyzer maydetermine the surface normals at any granularity and for any geometricunit that is captured in the current 3D mesh 235.

At step 406, the angle comparator 330, also included in the overhanganalysis engine 124, compares each of the dot products 315 to theoverhang angle threshold 231. Again, each of the dot products 315corresponds to a triangle specified in the current 3D mesh 235. If thedot product 315 associated with a particular triangle exceeds theoverhang angle threshold 231, then the angle comparator 330 considersthe triangle to be overhanging. Further, the magnitude of the dotproduct 315 corresponds to the significance of the overhang. Afterperforming the comparison operations, the angle comparator 330 convertsthe dot products 315 to overhang magnitudes 325 that range in valuebetween zero and one. If the angle comparator 330 does not consider aparticular triangle to be overhanging, then the angle comparator 330sets the value of the corresponding overhang magnitude to zero. Bycontrast, the angle comparator 330 translates the largest magnitude dotproducts 315 to overhang magnitudes 335 of one. In alternateembodiments, the angle comparator 330 may be configured to perform anytype of operation that yields deterministic information regarding therelative significance of overhangs in the current 3D mesh 235.

At step 408, the overhang shader 350 applies the overhang color map 301to the overhang magnitudes 325, generating the overhang shading 251. Theoverhang shading 251 provides an easily comprehensible, concise visualrepresentation of the significance of the overhang magnitudes 325per-triangle across the current 3D mesh 235. In alternate embodiments,the overhang shading 251 may be replaced with any visual means ofexpressing the overhang magnitudes 325. For instance, in alternateembodiments, the overhang shading 251 may be replaced with numbers andoutlines corresponding to the overhanging magnitudes 325.

At step 410, the diffuse shader 280 combines the overhang shading 251with diffuse shading to form the composite shading 281. In alternateembodiments, the diffuse shader 280 may incorporate any number and typesof shading, such as specular shading, into the composite shading 281.Further the diffuse shader 280 may perform shading operations in anytechnically feasible fashion. In other alternate embodiments, thediffuse shader 280 may perform any number and type of operations thatannotate the current 3D mesh 235 with relevant overhang data.

At step 412, the 3D model GUI 122 causes the display device 114 to showthe dynamically updated visualization 291 that reflects the compositeshading 281. At step 414, if the 3D model GUI 122 does not receive anydesigner modifications to the overhang angle threshold 231 and/or thecurrent 3D mesh 235, then the 3D printer 140 and the 3D support remover150 complete the 3D printing process based on the current 3D mesh 235.The method 400 then terminates.

If, at step 414, the 3D model GUI 122 receives designer modifications tothe overhang angle threshold 231 and/or the current 3D mesh 235, thenthe method 400 returns to step 404. The 3D model interactive tool 120cycles through steps 404 through 414, processing designer modificationsuntil the 3D model GUI 122 does not receive any further designermodifications. In this fashion, the 3D model interactive tool 120enables the designer to fine-tune the current 3D mesh 235 in aniterative manner. Advantageously, this fine-tuning allows the designerto efficiently evaluate design trade-offs and optimize the 3D objectgenerated by the 3D printing system 101.

Generating Support Posts

FIG. 5 is a conceptual diagram illustrating a three-dimensional (3D)model with highlighted overhangs 510 and a corresponding 3D model withsupport geometry 540, according to one embodiment of the presentinvention. Both the 3D model with highlighted overhangs 510 and the 3Dmodel with support geometry 540 depict the same 3D model117—representing a solid monster.

For explanatory purposes only, the context of FIG. 5 is that thedesigner generates the 3D model 117 via the 3D model generator 110. The3D model interactive tool 120 receives the 3D model 117 and the overhanganalysis engine 24 determines the overhanging regions of the 3D model117 that required buttressing. Notably, as part of the overhang angleanalysis, the 3D model interactive tool 120 uses a segmentationalgorithm to find explicit boundaries for the overhang regions. The 3Dmodel with highlighted overhangs 510 depicts each discrete overhangingregion with blue outlines and red fill. In alternate embodiments, the 3Dmodel interactive tool 120 may determine the overhanging points and/orregions in the 3D model 117 in any technically feasible fashion.

After the 3D model interactive tool 120 identifies the overhangingregions in the 3D object 117, the incremental graph generator 138, theangle analyzer 132, and the end point selector 134 work together tooptimize the selection of support posts to brace the 3D model 117.Subsequently, the support geometry generator 130 outputs the supportgeometry 140. The 3D model with support geometry 540 depicts thecombination of the 3D model 117 and the support geometry 140.

FIG. 6 is a conceptual diagram illustrating the incremental graphgenerator 138 of FIG. 1B, according to one embodiment of the presentinvention. The incremental graph generator 138 creates a support graph640 that subsequently acts as a blueprint for the support geometry 140.Advantageously, the incremental graph generator 138 optimizes thesupport graph 640 based on the capabilities of the 3D printer 150 tominimize both the material and time required for the 3D printer 150 togenerate the support geometry 140.

In operation, the incremental graph generator 138 receives the 3D model117, generates initial points 620, creates the support graph 640, andthen incrementally grows the support graph 640 in the downwarddirection. Subsequently, the support model generator 130 creates thesupport geometry 140 based on the support graph 640. The support modelgenerator 130 may generate the support geometry 140 in any technicallyfeasible fashion.

After receiving the 3D model 117, the incremental graph generator 138,in conjunction with the angle analyzer 132, determines the initialpoints 620. As shown, the initial points 620 include contact points 622,object points 624, and ground points 626. The contact points 622represent points on the surface of the 3D model 117 that are overhangingand require support during the printing process. The object points 624are points on the surface of the 3D model 117 that are relativelyhorizontal and thus are capable of bolstering surfaces of the 3D model117 that required support. And the ground points 626 are points on theground (i.e., the horizontal print bed) that may be used to counteractthe forces of gravity.

The angle analyzer 132 may generate the initial points 620 in anytechnically feasible fashion. For example, suppose that an“overhang_angle_threshold” were to reflect the maximum angle the 3Dprinter 150 were capable of generating without support. Further supposethat a “spacing_distance” were to reflect the maximum vertical distancespanned by the material exuded by the 3D printer 150 in a single step.In such a scenario, the angle analyzer 132 may determine the contactpoints 622 based on the following pseudo-code:

1) Find the set of triangles T where: a)DotProduct(triangle_face_normal,up_direction) >Cosine(overhang_angle_threshold) 2) For the set of triangles T, find allvertices that are local minima and add these vertices to the contactpoints. 3) Apply a reverse-watershed algorithm to cover the remainingtriangles of the 3D model with well-spaced contact points. For eachtriangle: a) Generate a set of sample points p. b) For each sample pointp, if the distance(p, contact points) > spacing_distance, then add p tocontact_points.As persons skilled in the art will recognize, this pseudo-code typicallygenerates optimized contact points 622 that comprehensively yetnon-contiguously cover the overhanging surfaces of the 3D model 117. Bycontrast, conventional approaches to generating support geometriesrepresent each overhanging surface as a single contiguous area.

In another example, suppose that a “max_object_angle” were to representa relatively horizontal surface on the 3D model 117 capable ofsupporting other surfaces of the 3D model 117, such as a surface that isat an angle of less than 60 degrees from the horizontal plane. In such ascenario, the angle analyzer 132 may determine the object points 624based on the following pseudo-code:

1) Find the set of triangles T where: a)DotProduct(triangle_face_normal, up_direction) >Cosine(max_object_angle) 2) Repeat loop: a) Generate a random point p onthe set of triangles T b) If distance(p, existing object points) >spacing_distance, then add p to object points Stop loop when (2b) hasfailed more than a predetermined number of times, indicating that therelatively horizontal surface is well represented.

In a final example, support that a “post_radius,” a “base_radius,” and a“tip_radius” were to represent, respectively, a target radius forsupport posts, a radius for the base of support posts, and a radius forthe tips of support posts (i.e., where they contact the surface of the3D model 117), In such a scenario, the angle analyzer 132 may generatethe ground points 626 based on the following pseudo-code:

1) Compute the 3D bounding box of the surface of the 3D model 2) Projectthe 3D bounding box onto the ground plane, creating a 2D polygon. 3)Generate a set of test points P within this 3D polygon, where the testpoints P are organized at the center-points of a hexagonal grid. 4) Foreach test point p in P: a) If the vertical truncated cone centered at pwith a predetermined base radius, base length, and tip radius does notinterest the surface of the 3D object, then add p to the ground points.

In alternative embodiments, the angle analyzer 132 may determine thecontact points 622, the object points 624, and the ground points 626 inany technically feasible fashion. Further, the predetermined thresholdsand dimensions, such as the overhang angle threshold 231, thepost_radius, the max_object_angle, etc. may be selected in any fashionthat is consistent with the capabilities of the 3D printer 150 andoptimizing the support geometry 140. Finally, the angle analyzer 132 maybe configured to determine the contact points 622, the object points624, and the ground 626 points in a dynamic fashion as the incrementalgraph generator 138 creates the support graph 640 instead of as part ofthe support graph 640 initialization process.

After determining the initial points 620, the incremental graphgenerator 138 creates the support graph 640. As shown, the support graph640 includes nodes 642 and edges 644. In general, the support graph 640is an abstract specification of a mesh of support posts—the supportgeometry 140. Each of the edges 644 connects two of the nodes 642,referred to herein as a start node of the edge 644 and an end node ofthe edge 644. The Y coordinate of the point represented by the startnode 642 is greater than or equal to the Y coordinate of the pointrepresented by the end node 642.

The incremental graph generator 138 initializes the support graph 640 toinclude no edges 644 and one node 642 for each of the initial points620. Consequently, the initial support graph 640 specifies no supportposts. As the incremental graph generator 138 grows the support graph640—judiciously adding to the edges 644 and the nodes 642—the supportgeometry 140 specified by the support graph 640 becomes increasinglycomprehensive. After the incremental graph generator 130 finishesgenerating the support graph 640, the support geometry 140 specified bythe support graph 640 fully supports the 3D model 117 during the 3Dprinting process.

In the support geometry 140 specified by the completed support graph640, each of the object points 624 are adequately bolstered againstgravity either directly via one support post or indirectly via asequential series of support posts. As persons skilled in the art willrecognize, one or more of the nodes 642 may not be connected to any ofthe edges 644. For example, one or more of the ground points 626 may notbe necessary as a foundation for the support structure 140. The supportgeometry generator 130 discards unused nodes 642 in the support graph640 prior to generating the support structure 140.

To ensure that each of the contact points 622 in the support graph 640are connected to the support structure 140 prior to the completion ofthe support graph 640, the incremental graph generator 138 adds thenodes 642 corresponding to the contact points 622 to an active list 652.The active list 652 represents the set of the nodes 642 that are“unterminated.” If a node 642 is unterminated, then the node 642requires support (i.e. does not correspond to any of the ground points626 or the object points 624) and is not a start node for any of theedges 644. The incremental graph generator 138 sorts the nodes 642included in the active list 652 in order of decreasing Y coordinate.Consequently, the first node 642 in the active list is the node 642 thatis both unterminated and has the highest Y coordinate among the nodes642 that are unterminated.

In operation, the incremental graph generator 138 dynamically maintainsthe active list 652 as a sorted queue of the nodes 642 that are notcompletely processed. The incremental graph generator 138 generates onenew edge 644 at a time-selecting the first node 642 from the active list652 as a new start node 642 and then removing the first node 642 fromthe active list 652. After the incremental graph generator 138 sets thenew start node 642, the end point selector 134 chooses an optimized endpoint. The incremental graph generator 138 then generates a new edge 644that connects the new start node 642 to the end node 342 representingthe optimized end point. The incremental graph generator 138 continuesto generate new edges 644 in this fashion until the incremental graphgenerator 138 determines that the active list 652 is empty and,therefore, the support graph 640 is complete.

The end point selector 134 determines an end point for each edge 644based on support criteria 610. As shown, the support criteria 610include a constraint cone 612, collision constraints 614, andoptimization criteria 616. In operation, the end point selector 134works in conjunction with the angle analyzer 132 to evaluate therelationships between various surfaces in the 3D model 117 and the nodes642 and edges 644 included in the dynamically growing support graph 640.Based on these relationships and the support criteria 610, the end pointselector 134 determines an end point for each support post thatoptimally leverages the capabilities of the 3D printer 150.

The cone constraint 612 ensures that the angle of the new edge 644 andthe ground plane does not exceed the overhang angle threshold 231. Thecone constraint 612 may be specified and applied in any technicallyfeasible fashion. For example, in one embodiment, the cone constraint612 is expressed as the following pseudo-code:

1) Place a code with the tip of the cone at the start point p orientedalong the Y axis and the cone opening angle equal to (0.5* PI − maximumoverhang threshold). 2) If an end point q is inside the code, then theend point q satisfies the cone constraint.

The collision constraints 614 ensure that the new edge 644 does not passwithin a “post tolerance” of any of the edges 644 in the support graph640. Further, the collision constraints 614 ensure that the new edge 644does not intersect the surface of the 3D model 117. In general, the posttolerance is expressed as the sum of the maximum post radius and a postbuffer that is specific to the 3D printer 150. The post tolerance andthe collision constraints 614 may be determined and implemented in anytechnically feasible fashion.

The optimization criteria 616 specify desirable qualities for the endpoints and support posts. In one embodiment, the optimization criteria136 favors end points that are as close to the surface of the 3D model117 as possible, thereby minimizing the area spanned by the 3D model 117combined with the support geometry 140. In such an embodiment, “close”may be defined as either Euclidean distance or Manhattan distance:

-   1) For two points, a=(x1, y1, z1) and b=(x2, y2, z2):-   a) Euclidean distance from a to b=√((x1−x2)²+(y1−y2)²+(z1−z2)²-   b) Manhattan distance from a to b=abs(x1−x2)+abs(y1−y2)+abs(z1−z2)

As persons skilled in the art will recognize, sagacious choices of theoptimization criteria 136 reduce both the time required for the 3Dprinter 150 to generate the 3D object and the cost of the supportmaterial associated with the support geometry 140.

As part of processing each start point, the end point selector 134identifies “potential” end points. First, the end point selector 134evaluates existing nodes 642 in the support graph 640 to determine thosenodes 642 that both lie within the constraint code 612 and satisfy thecollision constraints 614. If the end point selector 134 successfullyidentifies one or more potential end points, then the end point selector134 applies the optimization criteria 616 to select the potential endpoint that best meets the optimization criteria 616. After the end pointselector 134 identifies this “optimized” end point, the incrementalgraph generator 138 generates a new edge 644 that connects the node 642corresponding to the start point to the node 642 corresponding to theoptimized end point

If the end point selector 134 is unable to identify any potential endpoints from the nodes 642 included in the support graph 640, then theend point selector 134 generates an internal point 654. The end pointselector 134 chooses the internal point 654 in a manner that grows thesupport graph 640 downward (i.e., towards the ground) and inward (i.e.,toward the 3D model 117). Consequently, the end point selector 134 setsthe Y coordinate of the internal point 654 to a value that is lower thanthe Y coordinate of the start point. Further, the end point selector 134sets both the Y coordinate and the X coordinate of the internal point654 such that the internal point 654 lies within the constraint cone612, satisfies the collision constraints 614, and maximizes theoptimization criteria 616.

In some embodiments, the end point selector 134 incrementally extendsthe support graph 640 downward in a fixed Y increment. In one suchembodiment, the end point selector 134 sets the Y coordinate of theinternal point 654 to a distance two times the support post radius lowerthan the Y coordinate of the start point. In another embodiment, the endpoint selector 134 sets the Y coordinate of the internal point 654 tothe lowest Y coordinate of the constraint cone 612.

As persons skilled in the art will recognize, the optimization criteria616 may specify any technically feasible evaluation metric, and the endpoint selector 134 may implement a variety of strategies to choose theinternal point 654. For example, in one embodiment, the optimizationcriteria 616 configures the end point selector 134 to choose the Xcoordinate of the internal point 654 to be as close as possible to the Xcoordinate of the starting point. In another embodiment, theoptimization criteria 616 configures the end point selector 134 tochoose the internal point 654 to be as close as possible to the surfaceof the 3D model 117 at the lowest Y-coordinate of the constraint cone:

-   1) Slice the 3D model at the lowest Y coordinate of the constraint    cone-   2) Convert the 3D model and the constraint code into a 2D polygon    and circle, respectively-   3) Set the internal point coordinates to match the point in the    circle that is outside yet closest to the 2D polygon    In general, the goal of the optimization criteria 616 is to minimize    the time required for the 3D printer 150 to fabricate the union of    the 3D model 117 and the support geometry 140.

After the end point selector 134 creates the internal point 654, theincremental graph generator 138 creates a new node 644 corresponding tothe internal point 654 and creates a new edge 644 that connects the node642 corresponding to the internal point 654 to the start point. Further,the incremental graph generator 138 adds the internal point 654 to theactive list 652, maintaining the active list 652 in order of decreasingY coordinates.

The optimization techniques described herein are illustrative ratherthan restrictive, and may be modified to reflect various implementationswithout departing from the broader spirit and scope of the invention.For instance, suppose that the end point selector 134 were to select oneof the other nodes 642 in the active list 652 as the optimized endpoint. In such a scenario, the end point selector 134 may furtherfine-tune the support graph 640. More specifically, instead of directlyconnecting the start point to the optimized end point, the end pointselector 134 may indirectly connect the start point to the optimized endpoint. The end point selector 134 would create a new internal point 654at a Y-coordinate lower than either the start point or the optimized endpoint. The incremental graph generator 138 would then create two newedges 644. The first new edge 644 would connect the node 642corresponding to the start point to the node 642 corresponding to theinternal point 654. The second new edge 644 would connect the node 642corresponding to the internal node 654 to the node 642 corresponding tothe optimized end point.

When the incremental graph generator 138 determines that there are nonodes 642 remaining in the active list 652, the support model generator130 generates the support geometry 140 based on the now-completedsupport graph 640. More specifically, for each of the edges 644, thesupport model generator 130 generates the support post as a 3D tube. Insome embodiments, the support model generator 130 varies the width ofthe 3D tube to reduce the extent of the support material. For instance,the support model generator 130 may apply one or more support widthheuristics to determine a first support radius and a second supportradius. The first support radius corresponds to a minimum widthnecessary to adequately bolster the 3D object during fabrication. Thesecond support radius corresponds to a minimum width required foradequate contact with the 3D object. The support model generator 130then varies the width of the 3D tube representing the support post fromtop to bottom, selecting the first support radius for the middle of thesupport post and the second support radius for the start point and/orend points.

Notably, the angle of each of the support posts corresponds to the angleof the corresponding edge 644 and, consequently, the support geometry140 may include support posts at any angle. Typically, the supportgeometry 140 “hugs” the contours of the 3D model 117—thereby reducingboth the time required to fabricate the 3D object and the cost of thesupport material.

FIG. 7 is a conceptual diagram illustrating selection scenarios 710,720, and 730 that the end point selector 134 of FIG. 1 may be configuredto evaluate, according to one embodiment of the present invention. Aspreviously disclosed herein, the end point selector 134 identifiespoints that are located within the constraint cone 612 and satisfy thecollision constraints 614. Subsequently, the end point selector 134picks an optimized end point from these identified points based on theoptimization criteria 616. In some embodiments, the end point selector134 generates a new internal point 654 based on the optimizationcriteria 616.

In operation, the incremental graph generator 138 selects the first node642 in the active list 652 as the starting point. The starting point maybe one of the contact points 622 or one of the internal points 654.Based on the starting point, the end point selector 134 attempts toidentify an optimized end point that, when connected to the startingpoint via a new edge 644 in the support graph 640, will optimally extendthe support graph 640. As part of this selection process, the end pointselector 134 works together with the angle selector 132 to identifypoints that satisfy the support criteria 610, including the constraintcone 612, the collision constraints 614, and the optimization criteria616.

In one embodiment, the end point selector 134 preferentially selects apoint that is represented by one of the existing nodes 642 as theoptimized end point. If the end point selector 134 does not successfullyidentify such a viable “existing” point, then the end point selector 134generates a new internal point 654 and relays the internal point 654 tothe incremental graph generator 138. In alternate embodiments, the endpoint selector 134 may generate one or more potential internal points654, evaluate these potential internal points 654 in conjunction withexisting points, and select the optimized end point from both thepotential internal points 654 and the existing points.

For explanatory purposes only, the context of FIG. 4 is that theincremental graph generator 138 initially selects the contact point622(0) as the starting point. Based on the support criteria 610, theexisting state of the support graph 640, and the geometries included inthe 3D model 117, the end point selector 134 evaluates the threedifferent selection scenarios 710, 720, and 730.

First, as shown in selection scenario 710, the end point selector 134considers the ground point 626(0) as the optimized end point. Theselection scenario 710 depicts the contact point 622(0) connected to theground point 626(0). Subsequently, in selection scenario 720, the endpoint selector 134 considers the object point 624(0) as the optimizedend point. The selection scenario 720 depicts the contact point 622(0)connected to the object point 624(0). Finally, the end point selector134 elects to generate the internal point 654(0) instead of selectingeither the ground point 626(0) or the object point 624(0) as theoptimized end point.

After the end point selector 134 generates and selects the internalpoint 654(0) as the optimized end point for the contact point 622(0),the incremental graph generator 138 adds a new node 642 and a new edge644 to the support graph 640. This new node 642 corresponds to theinternal point 654(0), and the new edge 644 connects the contact point622(0) to the internal point 654(0). The incremental graph generator 138then selects a next starting point—the contact point 622(1)—and relaysthe contact point 622(1) to the end point selector 134 for pairing to anoptimized end point.

As depicted in selection scenario 730, the end point selector 134selects the existing internal point 654(0) as the optimized end pointfor the contact point 622(1). Subsequently, the incremental graphgenerator 138 grows the support graph 640—connecting the contact point622(1) to the internal point 654(0) via a second new edge 644.

Finally, the incremental graph generator 138 selects a third startingpoint—the internal point 654(0)—and relays the internal point 654(0) tothe end point selector 134 for pairing to an optimized end point. Theend point selector b 134 selects the object point 624(0) as theoptimized end point for the internal point 654(0), and the incrementalgraph generator 138 adds another new edge 644 to the support graph 640.This new edge 644 connects the internal point 654(0) to the object point624(0). As illustrated in FIG. 4, incrementally building the supportgraph 640 based on optimizing end points enables adequate buttressing ofboth the contract points 622(0) and 622(1) while streamlining thesupport geometry 140 to the contours of the 3D model 117.

FIGS. 8A-8B set forth a flow diagram of method steps for generatingsupport geometry to facilitate printing of a three-dimensional (3D)model, according to one embodiment of the present invention. Althoughthe method steps are described with reference to the systems of FIGS.1-4, persons skilled in the art will understand that any systemconfigured to implement the method steps, in any order, falls within thescope of the present invention.

As shown, a method 800 begins at step 802, where the support geometrygenerator 130 receives the 3D model 117. After receiving the 3D model117, the angle analyzer 132 included in the support geometry generator130 identifies the ground points 626 and the object points 624 that areincluded in the initial points 620. Notably, the identified objectpoints 624 correspond to surfaces of the 3D model 117 that arerelatively horizontal and, therefore, capable of supporting portions ofthe 3D model 117 at higher Y coordinates.

At step 804, the overhang analysis engine 124 identifies overhangingregions of the 3D model 117. The overhang analysis engine 124 mayidentify these overhanging regions in any technically feasible fashion.As part of step 804, the incremental graph generator 138 included in thesupport geometry generator 130 generates the contact points 622 thatspan each overhanging region. Advantageously, the incremental graphgenerator 138 maximizes the spacing of the contact points 622 tominimize the surface area of each overhanging region that is directlyconnected to the support geometry 140.

At step 806, the incremental graph generator 138 initializes the supportgraph 640. In particular, the incremental graph generator 138 generatesone node 642 for each of the contact points 622, the object points 624,and the ground points 626. The support graph 640 in this initial stateincludes no edges 644. At step 808, the incremental graph generator 138sets the active list 652 to include the contact points 622. Thus, theactive list 652 represents the points on the surface of the 3D model 117that require support to enable the 3D printer 150 to generate a quality3D object for the 3D model 117.

At step 810, the incremental graph generator 138 sorts the nodes 642included in the active list 652 by decreasing vertical coordinates.After the incremental graph generator 138 completes this sort, the firstnode 642 in the active list 652 is at the highest height of the nodes642 in the active list 652. Correspondingly, the last node 642 in theactive list 652 is at the lowest height of the nodes 642 in the activelist 652. As the incremental graph generator 138 incrementally grows thesupport graph 640, the incremental graph generator 138 maintains theactive list 652 as a sorted queue representing the nodes 642 in thesupport graph 640 that are unterminated.

At step 812, the incremental graph generator 138 sets a start node 642to the first node 642 in the active list 652 and removes the first node642 from the active list 652. At step 814, the end point selector 134included in the support geometry generator 130 evaluates the pointcorresponding to the start node 642 in conjunction with the supportcriteria 610, the existing support graph 640, and the 3D model 117 todetermine an optimized end point. Notably, the end point selector 134chooses an optimized end point that is located with the constraint cone612, complies with the collision constraints 614, and reflects theoptimization criteria 616. Notably, the end point selector 134 may electto generate a new internal point 654 as the optimized end point.

At step 816, the incremental graph generator 138 updates the supportgraph 640 and the active list 652 to reflect a new edge 644 thatconnects the start node 642 to the node 642 corresponding to theoptimized end point. As part of step 816, if the optimized end point isnot included in the support graph 640 (i.e., the optimized end point isa new internal point 654), then the incremental graph generator 138 addsa new node 642 that represents the optimized end point to the supportgraph 640. Further, if the optimized end point is included in neitherthe ground points 626 nor the object points 624, then the supportgeometry generator 130 adds the node 642 representing the optimized endpoint to the active list 652. Thus, the incremental graph generator 138queues the optimized end point for later reprocessing as a start point.

At step 818, if the incremental graph generator 138 determines that theactive list 652 is empty, then the method 800 proceeds to step 820. Atstep 820, the support geometry generator 130 creates the supportgeometry 140 corresponding to the completed support graph 640. Notably,the support geometry generator 130 creates a support post for each ofthe edges 644 included in the support graph 640. The support geometrygenerator 130 may generate the support geometry 140 in any technicallyfeasible fashion that is consistent with the fabrication constraints(e.g. minimum structure width, etc.) of the 3D printer 150.

If, at step 818, the incremental graph generator 138 determines that theactive list 652 is not empty, then the method 800 returns to step 812,where the incremental graph generator 138 processes the first node 642in the active list 652 as the start node 642. The support geometrygenerator 130 cycles through steps 812-818, processing nodes 642 in theactive list 652 until the active list 652 is empty and the support graph640 is complete.

FIG. 9 is a flow diagram of method steps for selecting an optimized endpoint for a support structure that facilitates printing of athree-dimensional (3D) model, according to one embodiment of the presentinvention. Although the method steps are described with reference to thesystems of FIGS. 1-4, persons skilled in the art will understand thatany system configured to implement the method steps, in any order, fallswithin the scope of the present invention.

As shown, a method 900 begins at step 902, where the end point selector134 receives the 3D model 117 and a start point. The start point may beany contact point 622 on the surface of the 3D model 117 that isoverhanging and requires support to prevent gravity-related artifactsduring 3D printing. Alternatively, the start point may be an internalpoint 654 in the incrementally-generated support graph 640 that is notyet connected to a suitable support point, such as one of the groundpoints 626 or the relatively-horizontal object points 624.

At step 904, the end point selector 134 attempts to identify one or moreacceptable candidate points from the points represented by the nodes 642included in the support graph 640. Each acceptable candidate point lieswithin the constraint cone 612 and satisfies the collision constraints614. As outlined previously herein, the constraint cone 612 specifies aregion that satisfies any desirable restrictions on the location of thesupport geometry 140. For instance, the constraint cone 612 may be a 3Dcone with the tip at the start point, oriented along the vertical axis,with both a cone opening angle and a height based on the capabilities ofthe 3D printer 150. And, for each candidate point, the collisionconstraints 612 ensure that if the candidate point were to be connectedto the start point via a support post, then the support post would notintersect the 3D model 117.

At step 906, if the end point selector 134 determines that there are oneor more candidate points, then the method 900 proceeds to step 908. Atstep 908, the end point selector 134 calculates the Manhattan distanceof each candidate point to the start point. The end point selector 134then selects the candidate point at the closest Manhattan distance tothe start point as the end point. In alternate embodiments, the endpoint selector 134 may evaluate the candidate points and then select theend point in any technically feasible fashion. For example, the endpoint selector 134 may calculate the Euclidian distance of eachcandidate point to the start point and subsequently select the candidatepoint at the closest Euclidian distance to the start point as the endpoint.

If, at step 908, the end point selector 134 determines that there are nocandidate points, then the method 900 proceeds to step 910. At step 910,the end point selector 134 creates the internal point 654 andinitializes the Y coordinate of the internal point 654 to the lowest Ycoordinate within the constraint cone 612. Setting the Y coordinate inthis fashion situates the internal point 654 at the furthest allowablevertical distance from the start point and, therefore, the closestallowable vertical distance to the ground. At step 912, the end pointselector 134 establishes a region of potential X coordinates for theinternal point 654 that both situate the internal point 134 within theconstraint cone 612 and satisfy the collision constraints 614. The endpoint selector 134 then selects the potential X coordinate that situatesthe new point as close to the surface of the 3D model 117 as possible.At step 914, the end point selector 134 sets the end point to theinternal point 654.

In sum, the disclosed techniques may be used to automate portions of the3D object design process. In operation, an overhang analysis enginecalculates the dot products of the surface normal vs the up directionfor different triangles included in a 3D mesh that represents a 3Dobject. The overhang analysis engine compares these dot products to aconfigurable overhang angle threshold. This overhang angle threshold istypically selected to reflect the maximum angle that a particular 3Dprinter is configured to generate 3D solid objects without addingsupport material and, optionally, a “safety” margin. The differencesbetween the dot products and the overhang angle threshold reflect thedegree with which each triangle included in the 3D mesh exceeds theoverhang angle threshold. The overhang analysis engine then generatesoverhang shading that visually represents the relative impact ofoverhangs on the 3D object extruded by the 3D printer.

A diffuse shader composites the overhang shading with the diffuseshading associated with the 3D mesh to create overall shading.Subsequently, a 3D model graphic user interface visually displays theshaded 3D mesh—enabling the designer to easily identify those portionsof the 3D mesh requiring support material. Various 3D mesh modificationtools and an overhang angle threshold selector enable the designer toquickly alter the 3D mesh and the overhang angle threshold to reduce theextent or structure of the required support material. For instance, thedesigner may perform sculpting operations on the 3D mesh to reduceoverhang angles or add support columns to the 3D mesh, thus controllingthe type of support structures. Alternatively, the designer may adjustthe overhang angle threshold to correspond to a larger overhang anglethreshold associated with a more advanced 3D printer. Upon adjusting the3D model 117 or the overhang angle threshold, the overhang analysisengine re-computes the overhang shading, and the 3D mesh GUI redisplaysthe 3D mesh with the updated composite shading.

Advantageously, automating overhang analysis and visually highlightingpotentially problematic regions in the 3D mesh increases both thelikelihood of producing high quality 3D objects and the time required tofine-tune 3D meshes. In particular, designers may use automated tools toefficiently direct re-design efforts to reduce the extent of supportmaterial generated by 3D printers. And, in general, reducing the extentof the support material reduces aesthetic (e.g., incorrect textures)and/or functional (e.g., drooping) defects associated with removal ofthe support material to reveal the final 3D object. Further, enablinginteractive modifications of both the 3D mesh and the overhang anglethreshold facilitates quickly and accurately assessing the impact ofdifferent 3D models and 3D printers on the quality of generated 3Dobjects.

Further, the disclosed techniques may be used to create supportstructures designed to be efficiently exuded by 3D printers whileensuring the integrity of 3D models throughout the fabrication process.Again, the overhang angle threshold reflects fabrication limitations ofa 3D printer. Accordingly, the overhanging surfaces identified by theoverhang analysis engine require support as the 3D printer fabricatesthe 3D object specified by the 3D model. After the overhang analysisengine has identified the overhanging surfaces, a support geometrygenerator creates a support graph that is a blueprint for an optimizedsupport structure for the 3D model.

The support geometry generator creates the support graph in anincremental process—starting at the topmost overhanging surface andproceeding towards the ground. The support graph includes edges betweencontact nodes representing the overhanging surfaces and additional nodesrepresenting points on stabilizing surfaces capable of buttressing theoverhanging surfaces. These stabilizing surfaces include the 3D printingsurface (i.e. the ground) and relatively horizontal 3D model surfaces.As part of expanding the support graph downwards, the support geometrygenerator may generate internal, lower, nodes and then connect theexisting support graph nodes to these internal nodes. After generatingthe support graph, the support geometry generator translates each of theedges into a support post with a width that minimally, yet effectively,supports the connected overhanging structures. Together, these supportposts form an optimized support structure.

In some embodiments, the support geometry generator includesoptimization criteria to minimize the volume spanned by the 3D modelcombined with the support structure. Again, the support geometrygenerator may insert internal nodes as part of growing the graphdownwards. In such scenarios, the support geometry generator detects andexploits flexibility in the selection of the internal nodes to grow thesupport graph inward as opposed to outwards. In particular, the supportgeometry generator selects internal nodes that connect to the existinggraph by edges that are as close to the surface of the 3D model aspossible—without violating any constraints. The constraints, such aslimiting the angle between each edge and the ground plane, ensure thatthe generated support structure is both cohesive and separable from the3D model.

Advantageously, the timed required for a 3D printer to generate supportmaterial for a set of interconnected support posts that spans aparticular volume is typically much less than the timed required for the3D printer to generate support material that homogenously fills thevolume. Consequently, the disclosed techniques for generating sparsesupport structures enable 3D printers to more efficiently fabricaterobust 3D models than conventional techniques that rely on relativelydensely packed support structures. Further, since sparse supportstructures include less support material than dense support structures,the cost of fabricating 3D models with interconnected support posts isreduced compared to fabricating 3D models with conventional supportstructures. Judiciously selecting the angles of support posts to reducegaps between the support posts and the boundaries of the 3D objectfurther reduces both the time required to generate the 3D object and thecost of the associated support material.

One embodiment of the invention may be implemented as a program productfor use with a computer system. The program(s) of the program productdefine functions of the embodiments (including the methods describedherein) and can be contained on a variety of computer-readable storagemedia. Illustrative computer-readable storage media include, but are notlimited to: (i) non-writable storage media (e.g., read-only memorydevices within a computer such as compact disc read only memory (CD-ROM)disks readable by a CD-ROM drive, flash memory, read only memory (ROM)chips or any type of solid-state non-volatile semiconductor memory) onwhich information is permanently stored; and (ii) writable storage media(e.g., floppy disks within a diskette drive or hard-disk drive or anytype of solid-state random-access semiconductor memory) on whichalterable information is stored.

The invention has been described above with reference to specificembodiments. Persons of ordinary skill in the art, however, willunderstand that various modifications and changes may be made theretowithout departing from the broader spirit and scope of the invention asset forth in the appended claims. The foregoing description and drawingsare, accordingly, to be regarded in an illustrative rather than arestrictive sense.

Therefore, the scope of embodiments of the present invention is setforth in the claims that follow.

The invention claimed is:
 1. A method for selecting support pointsincluded in support structures that is implemented by a computer whenprinting three-dimensional models, the method comprising: applying, viaa processor, a first constraint to a first unsupported point included ina support structure to identify a candidate region, wherein the supportstructure is connected to a three-dimensional model; evaluating thecandidate region to determine a first support point, wherein the firstsupport point comprises a point included within the candidate regionthat is closest to the three-dimensional model; generating a firstsupport post between the first unsupported point and the first supportpoint; and causing at least one of the three-dimensional model and thefirst support post to be printed by a three-dimensional printer.
 2. Themethod of claim 1, wherein the first constraint comprises a verticaldistance between the first unsupported point and the candidate region.3. The method of claim 2, wherein the candidate region comprises ahorizontal plane.
 4. The method of claim 1, wherein the first constraintcomprises a maximum acceptable angle of a line relative to a horizontalground plane, wherein the line extends from the first unsupported pointto the first support point.
 5. The method of claim 1, wherein the firstconstraint comprises a minimum acceptable distance between the firstunsupported point and any point included in the three-dimensional model.6. The method of claim 1, wherein the first support post resides at anangle that is less than ninety degrees relative to a horizontal groundplane.
 7. The method of claim 1, wherein the first unsupported point islocated within an overhanging surface of the three-dimensional model. 8.The method of claim 1, further comprising: applying a second constraintto a second unsupported point included in the support structure toidentify both a first candidate point and a second candidate point;calculating a first Manhattan distance between the first candidate pointand the second unsupported point; calculating a second Manhattandistance between the second candidate point and the second unsupportedpoint; comparing the first Manhattan distance and the second Manhattandistance; and if the first Manhattan distance exceeds the secondManhattan distance, then generating a second support post between thesecond unsupported point and the second candidate point, or if the firstManhattan distance does not exceed the second Manhattan distance, thengenerating a second support post between the second unsupported pointand the second candidate point.
 9. The method of claim 8, wherein thesecond candidate point is located within either a horizontal groundplane or the three-dimensional model.
 10. One or more non-transitorycomputer-readable storage media including instructions that, whenexecuted by one or more processing units, cause the one or moreprocessing units to select support points included in support structuresimplemented when printing three-dimensional models by performing thesteps of: applying a first constraint to a first unsupported pointincluded in a support structure to identify a candidate region, whereinthe support structure is connected to a three-dimensional model;evaluating the candidate region to determine a first support point,wherein the first support point comprises a point included within thecandidate region that is closest to the three-dimensional model;generating a first support post between the first unsupported point andthe first support point; and causing at least one of thethree-dimensional model and the first support post to be printed by athree-dimensional printer.
 11. The one or more non-transitorycomputer-readable storage media of claim 10, wherein the firstconstraint comprises a vertical distance between the first unsupportedpoint and the candidate region.
 12. The one or more non-transitorycomputer-readable storage media of claim 11, wherein the candidateregion comprises a horizontal plane.
 13. The one or more non-transitorycomputer-readable storage media of claim 10, wherein the firstconstraint comprises a maximum acceptable angle of a line relative to ahorizontal ground plane, wherein the line extends from the firstunsupported point to the first support point.
 14. The one or morenon-transitory computer-readable storage media of claim 10, wherein thefirst constraint comprises a minimum acceptable distance between thefirst unsupported point and any point included in the three-dimensionalmodel.
 15. The one or more non-transitory computer-readable storagemedia of claim 10, wherein the first support post resides at an anglethat is less than ninety degrees relative to a horizontal ground plane.16. The one or more non-transitory computer-readable storage media ofclaim 10, wherein the first unsupported point is located within anoverhanging surface of the three-dimensional model.
 17. The one or morenon-transitory computer-readable storage media of claim 10, furthercomprising: applying a second constraint to a second unsupported pointincluded in the support structure to identify both a first candidatepoint and a second candidate point; calculating a first Manhattandistance between the first candidate point and the second unsupportedpoint; calculating a second Manhattan distance between the secondcandidate point and the second unsupported point; comparing the firstManhattan distance and the second Manhattan distance; and if the firstManhattan distance exceeds the second Manhattan distance, thengenerating a second support post between the second unsupported pointand the second candidate point, or if the first Manhattan distance doesnot exceed the second Manhattan distance, then generating a secondsupport post between the second unsupported point and the secondcandidate point.
 18. The one or more non-transitory computer-readablestorage media of claim 17, wherein the second candidate point is locatedwithin either a horizontal ground plane or the three-dimensional model.19. A system configured to select support points included in supportstructures implementing when printing three-dimensional models, thesystem comprising: a memory that includes instructions; a processingunit that is coupled to the memory and, when executing the instructions,is configured to: apply a first constraint to a first unsupported pointincluded in a support structure to identify a candidate region, whereinthe support structure is connected to a three-dimensional model,evaluate the candidate region to determine a first support point,wherein the first support point comprises a point included within thecandidate region that is closest to the three-dimensional model,generate a first support post between the first unsupported point andthe first support point, cause at least one of the three-dimensionalmodel and the support structure to be printed by a three-dimensionalprinter; and a three-dimensional printing unit coupled to the processingunit and configured to implement the three-dimensional model and thesupport structure.
 20. The system of claim 19, wherein the firstconstraint comprises a maximum acceptable angle of a line relative to ahorizontal ground plane, wherein the line extends from the firstunsupported point to the first support point.